A conventional ultrasound imaging system includes an array of ultrasonic transducers that transmit an ultrasound wave (a transient pressure wave) during a transmit mode and receive a reflected wave reflected from an object under study during a receive mode. The spatial response to this ultrasound wave is referred to as an ultrasound beam. In general, the overall (two-way) beam is a combination of two separate beams: a transmit beam, which represents the degree to which energy is deposited in the object, and a receive beam, which represents a system response to echoes originating at various points in space. The signals generated by the transducers responsive to the received pressure wave are processed and the results displayed as a visual image of the object.
The array typically includes a multiplicity of transducers configured as a linear array or row, each transducer driven by a separate signal voltage during the transmit mode. Selecting a time delay (relative to a reference time) for the signal voltage applied to each transducer controls a direction of the ultrasonic beam energy transmitted by the individual transducers. In addition, controlling the amplitude of the signal voltage applied to each transducer can be used to lower energy present in sidelobes of the ultrasound beam.
Controlling the time delay steers the ultrasonic energy emitted by the transducers to produce a net ultrasonic wave that travels along (scans) the object in a desired direction or along a scan line (also referred to as an A-line), with the energy focused at a selected point on the scan line. That is, the transmit energy is focused or concentrated at a fixed range (fixed focal point) from the transducer array, maximally localizing the energy at that range. At other ranges (distances from the transducer array) the energy is localized to a lesser extent, producing a broader beam. Thus although the energy is focused at only a single point on the scan line, the energy at proximate points (the points comprising a focal zone) may be sufficient to produce a reflected beam that can be processed to render an image with sufficient lateral resolution.
Similar beam-combining principles are employed when the transducers receive the reflected ultrasonic energy from the scan line. The voltages produced at the receiving transducers are controllably delayed and summed so that the net received signal response is primarily representative of the ultrasonic energy reflected from a single focal zone along the scan line of the object.
To generate a two dimensional or planar image of the object (and recognizing that ultrasound imaging occurs in the near field), during the receive mode the transducers are dynamically focused at successive ranges from the transducer array (depths into the object being scanned) along the scan line as the reflected ultrasonic waves are received. The focused range is based on the round-trip travel time of the ultrasound pulse. Controlling the time-delay associated with each transducer focuses the received energy at the desired time-variant range or depth. Such dynamic focusing in the receive mode produces a usable response at the focal point and a range of distances near the focal point. The range over which the two-way response of the system is well-focused is referred to as the depth of field. Outside the depth of field the image quality suffers and the reflections are not usable to produce the image.
As can be appreciated, the instantaneous beam steering and signal combining capabilities of the linear transducer array are capable of producing only a 2D image of the object, where the image is in the plane normal to the array surface and contains the centers of the array elements.
The planar two-dimensional image formed by the standard linear transducer array can typically be updated tens of times per second. The update rate is limited by the time required for the transmitted ultrasound pulse to travel to and back from the farthest image range point (the round-trip travel time). In an echocardiogram application, for example, the update rate (also referred to as the frame rate) determines the fidelity with which motion of the heart can be depicted. A frame rate of about 30 frames per second produces the effect of real-time motion, including real time motion of the heart. Higher frame rates are required only in special diagnostic situations.
The pulse travel time (and therefore the frame rate) is further dependent on the speed of sound through the imaged tissue. Assuming a typical 70-degree sector image including 128 separate ultrasound scan lines imaged to a depth of 10 centimeters, the time interval between successive image frames (frame updates) must be long enough to permit the sound pulse to travel a distance of:128×10 cm×2=2560 cm=25,600 mm.
The speed of sound in tissue is about 1.54 mm/μsec, therefore at least 16.62 milliseconds must be allowed for acquisition of the data to construct a single frame in the exemplary application. Since a frame rate of 30 frames per second allows 33.3 milliseconds to acquire each frame, the exemplary scenario can easily generate images at the desired rate of 30 frames/second.
Certain ultrasound imaging systems generate multiple transmit focal zones, i.e., where the transmit beam is focused at different ranges during the transmitting mode. This practice may limit the frame update rate. Ultrasound images are formed by combining the reflected energy from the multiple focal zones into a single image (or frame) focused at all ranges. The use of such multiple transmit focal zones requires that multiple beams be formed in each insonified direction during each image scan, possibly requiring reducing the frame below the desired 30 frames per second.
Real-time, three-dimensional ultrasound images (referred to as 4D images) are formed with a planar transducer array with each real time image frame including a volumetric 3D image. Such images have been commonly produced and displayed for obstetrics applications. More recently, such images have been introduced in echocardiology.
Although it is desired to provide such volumetric 3D images in cardiology applications, the frame rate limitations in real-time 3D imaging do not allow sufficient time to insonify the entire heart volume (also referred to as a source volume), receive and process the echoes and reproduce the real time image therefrom. For example, assume in a 3D image it is desired to image 128 planes with 128 lines per plane to produce the desired image volume. The acquisition of 16,384 (128×128) lines of ultrasound data to a depth of 10 cm requires more than two seconds. Thus the desired frame rate of 30 frames per second cannot be maintained.
To overcome the acquisition time penalty and produce displays with information comparable to 2D images, it is known to construct biplane images in lieu of real time 3D volumetric images. In this display mode two orthogonal planes are insonified and the resulting images displayed. These two images are easily formed using a planar array, since the array can be beam steered in any direction, while requiring only twice as many ultrasound lines as the standard image. Thus the desired high frame rates can be achieved. With some practice, an operator can mentally construct a 3D image of the heart from the two biplane images, but this is very difficult for the novice or occasional user.
It is also known to accelerate ultrasound imaging acquisition using beam multiplexing. According to this scheme, a single, wide main lobe transmit beam is formed and multiple parallel receive beams record the echoes generated by the acoustic energy in the main beam. When there are N receive beams for each transmit beam the process is referred to as N-to-1 beam multiplexing. The resulting two-way response is the product of the receive beam and the transmit beam. If the receive beam pattern is entirely within the main lobe of the transmit beam, then the overall response is simply the receive beam pattern since the transmit main lobe energy is relatively constant. This is referred to as a one-way beam pattern.
The side lobe energy of the one way beam will be higher, in general, than the side lobe energy of the two-way beam pattern, for which the transmit and receive side lobes occur in the same directions and therefore attenuate each other.
If the side lobe energy of the one-way response is normalized to the maximal one-way response, which is at the peak of the main lobe, then the products of the sidelobes of the transmit and receive beams (which individually represent responses less than unity) are lower than the sidelobes of the receive beam alone. Even though the sidelobes of the two-way beam pattern are in the same direction, the two-way side lobe response is lower relative to the maximal main response of the two-way beams.
One approach to volumetric echocardiology imaging synchronizes image acquisition to an EKG (electrocardiogram) and collects only a quarter of the 3D volumetric imaging during each heart cycle using 4-to-1 beam multiplexing. That is, during each heart cycle three-quarters of the displayed image is taken from a recording of one of three prior heart cycles. Only one-quarter of the displayed image is a real-time image. While there are certain known disadvantages with this approach, it can produce images at an adequate frame rate.
Given the current limitations in the art, there is clearly a need for a technology that allows high frame rate visualization of a volumetric cardiac image using an ultrasound planar array.
Deformable models are known in the art and were first used in computer animation to produce realistic motion of an elastic object. A deformable model models elastic object surfaces using connected mass elements according to various physics-based or geometric techniques. As illustrated in FIG. 1, an object surface 8 is modeled as grids of point masses 10. Each mass is connected to one or more adjacent masses by a rigid elastic rod 12 that exerts a return force on the connected masses when bent, stretched or compressed away from its rest state. Different masses can also be connected by other exemplary connecting rods.
The dynamics of the surface 8 can be defined at each mass by a force balance equation such as:
                              m          ⁢                      x            ¨                          +                  k          ⁢                      x            .                                      ︸                              forces            ⁢                                                  ⁢            from                                object            ⁢                                                  ⁢            dynamics                                +                  δ        ⁢                                  ⁢                  E          ⁡                      (            x            )                                      ︸                  internal          ⁢                                          ⁢          force                      =            f      user              ︸              external        ⁢                                  ⁢        force            where x is a position vector of the masses, m is the mass of each point or particle, k is a viscous friction constant (often assumed to be zero) and the variational symbol δE(x) is a restoring force proportional to the local curvature of the surface at the location of the point mass. The dots represent vector component-wise time derivatives. The variable x and the x-dot variables are vectors in a three dimensional space that describe the instantaneous condition (location, velocity, acceleration, etc.) of the model at any instant in time. Generally, the state equations defining the deformable model are derived from the force balance equation and consist of state variables and their derivatives.
This equation depicts the balance of forces resulting from motion of the point masses, restoring forces arising from the curvature of the surface at the location of the point mass and external forces controlling motion of the modeled object. For the computer animation application, external forces are specified by the animator. For medical image analysis, the external forces arise from a potential field derived from the image. In an ultrasound image, for example, the masses are attracted to regions of the image that depict strong echoes, but are not attracted to dark regions of the image depicting relatively weak echoes. That is, the echo magnitude is regarded as a type of charge and the oppositely charged point masses of the image boundaries are attracted to it.
The model set forth in the equation above allows the state variables (e.g., acceleration, velocity and position of the masses) to evolve in response to the various forces that act on them. This evolution is simulated by a discrete-time computational process in which the continuous-time state transition matrix associated with the equations of motion above is integrated to form a discrete time system matrix. Each time a multiplication of the state vector by this matrix is performed, new external force information can be incorporated into the computation as a discrete time driving function. The details of such discrete time systems are well known. For example, consult Digital Control of Dynamic Systems, by G. F. Franklin and J. D. Powell (Addison Wesley, 1980).